{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/jkrehbiel/Dropbox/Unpopular Courts Paper/Unpopular Courts AJPS/BJPS R&R/BJPS Final Manuscript Documents/Replication Materials/Log File.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}30 Jan 2020, 13:28:27

{com}. import delimited "/Users/jkrehbiel//Dropbox/Unpopular Courts Paper/Unpopular Courts AJPS/BJPS R&R/BJPS Final Manuscript Documents/Replication Materials/BJPS_replication_data.csv", clear
{res}{text}(32 vars, 3861 obs)

{com}. 
. *Model 1

. logit ecj_int1 c.sumcaseobs1 , vce(cluster case_celex)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2524.0191}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2519.2532}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2519.2475}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2519.2475}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      3861
{txt}{col 51}Wald chi2({res}1{txt}){col 67}= {res}      6.24
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0125
{txt}Log pseudolikelihood = {res}-2519.2475{txt}{col 51}Pseudo R2{col 67}= {res}    0.0019

{txt}{ralign 78:(Std. Err. adjusted for {res:1599} clusters in case_celex)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    ecj_int1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}sumcaseobs1 {c |}{col 14}{res}{space 2}-1.022872{col 26}{space 2} .4094922{col 37}{space 1}   -2.50{col 46}{space 3}0.012{col 54}{space 4}-1.825462{col 67}{space 3}-.2202821
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.4451206{col 26}{space 2} .0658854{col 37}{space 1}   -6.76{col 46}{space 3}0.000{col 54}{space 4}-.5742536{col 67}{space 3}-.3159877
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *Model 2

. logit ecj_int1 c.sumcaseobs1 c.netint  i.agproint i.agantiint i.freegoods_guum i.agri_guum i.freework_guum i.estab_guum i.services_guum i.capital_guum i.transport_guum i.compet_guum i.tax_guum i.socialprov_guum i.environment_guum i.consum_guum c.lastelectionpartycompetition c.eu_support i.court_size i.countrycode , vce(cluster case_celex)

{txt}note: 17.countrycode != 0 predicts failure perfectly
      17.countrycode dropped and 1 obs not used

note: 19.countrycode != 0 predicts failure perfectly
      19.countrycode dropped and 17 obs not used

note: 21.countrycode != 0 predicts failure perfectly
      21.countrycode dropped and 2 obs not used

note: 22.countrycode != 0 predicts failure perfectly
      22.countrycode dropped and 1 obs not used

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2497.3435}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1585.6464}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1566.0321}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1565.9399}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1565.9399}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      3808
{txt}{col 51}{help j_robustsingular##|_new:Wald chi2(37)}{col 67}=          {res}.
{txt}{col 51}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-1565.9399{txt}{col 51}Pseudo R2{col 67}= {res}    0.3730

{txt}{ralign 80:(Std. Err. adjusted for {res:1587} clusters in case_celex)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}      ecj_int1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      z{col 48}   P>|z|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}sumcaseobs1 {c |}{col 16}{res}{space 2}-1.531468{col 28}{space 2} .6355463{col 39}{space 1}   -2.41{col 48}{space 3}0.016{col 56}{space 4}-2.777116{col 69}{space 3}-.2858205
{txt}{space 8}netint {c |}{col 16}{res}{space 2} 2.947704{col 28}{space 2} .5868898{col 39}{space 1}    5.02{col 48}{space 3}0.000{col 56}{space 4} 1.797422{col 69}{space 3} 4.097987
{txt}{space 4}1.agproint {c |}{col 16}{res}{space 2} 3.549836{col 28}{space 2} .1293377{col 39}{space 1}   27.45{col 48}{space 3}0.000{col 56}{space 4} 3.296338{col 69}{space 3} 3.803333
{txt}{space 3}1.agantiint {c |}{col 16}{res}{space 2} .5265209{col 28}{space 2} .1356182{col 39}{space 1}    3.88{col 48}{space 3}0.000{col 56}{space 4}  .260714{col 69}{space 3} .7923277
{txt}1.freegoods_~m {c |}{col 16}{res}{space 2}-.1279012{col 28}{space 2} .1798637{col 39}{space 1}   -0.71{col 48}{space 3}0.477{col 56}{space 4}-.4804275{col 69}{space 3} .2246251
{txt}{space 3}1.agri_guum {c |}{col 16}{res}{space 2}-.0810136{col 28}{space 2} .1796359{col 39}{space 1}   -0.45{col 48}{space 3}0.652{col 56}{space 4}-.4330936{col 69}{space 3} .2710664
{txt}1.freework_g~m {c |}{col 16}{res}{space 2} .5526427{col 28}{space 2} .2072354{col 39}{space 1}    2.67{col 48}{space 3}0.008{col 56}{space 4} .1464689{col 69}{space 3} .9588166
{txt}{space 2}1.estab_guum {c |}{col 16}{res}{space 2}-.1559937{col 28}{space 2} .2037867{col 39}{space 1}   -0.77{col 48}{space 3}0.444{col 56}{space 4}-.5554083{col 69}{space 3} .2434208
{txt}1.services_g~m {c |}{col 16}{res}{space 2} .2552511{col 28}{space 2} .2243806{col 39}{space 1}    1.14{col 48}{space 3}0.255{col 56}{space 4}-.1845268{col 69}{space 3}  .695029
{txt}1.capital_guum {c |}{col 16}{res}{space 2} .2570916{col 28}{space 2} .2619021{col 39}{space 1}    0.98{col 48}{space 3}0.326{col 56}{space 4} -.256227{col 69}{space 3} .7704102
{txt}1.transport_~m {c |}{col 16}{res}{space 2}-.3808811{col 28}{space 2} .2813516{col 39}{space 1}   -1.35{col 48}{space 3}0.176{col 56}{space 4}  -.93232{col 69}{space 3} .1705579
{txt}{space 1}1.compet_guum {c |}{col 16}{res}{space 2}-.4779075{col 28}{space 2} .1763641{col 39}{space 1}   -2.71{col 48}{space 3}0.007{col 56}{space 4}-.8235748{col 69}{space 3}-.1322402
{txt}{space 4}1.tax_guum {c |}{col 16}{res}{space 2} .3535151{col 28}{space 2} .1814376{col 39}{space 1}    1.95{col 48}{space 3}0.051{col 56}{space 4}-.0020961{col 69}{space 3} .7091263
{txt}1.socialprov~m {c |}{col 16}{res}{space 2} .6716307{col 28}{space 2} .2184933{col 39}{space 1}    3.07{col 48}{space 3}0.002{col 56}{space 4} .2433916{col 69}{space 3}  1.09987
{txt}1.environmen~m {c |}{col 16}{res}{space 2} .4526091{col 28}{space 2} .2540134{col 39}{space 1}    1.78{col 48}{space 3}0.075{col 56}{space 4} -.045248{col 69}{space 3} .9504661
{txt}{space 1}1.consum_guum {c |}{col 16}{res}{space 2}-.0090658{col 28}{space 2} .2436107{col 39}{space 1}   -0.04{col 48}{space 3}0.970{col 56}{space 4}-.4865339{col 69}{space 3} .4684023
{txt}lastelection~n {c |}{col 16}{res}{space 2} .2044985{col 28}{space 2} 1.071484{col 39}{space 1}    0.19{col 48}{space 3}0.849{col 56}{space 4}-1.895572{col 69}{space 3} 2.304569
{txt}{space 4}eu_support {c |}{col 16}{res}{space 2}-.0112933{col 28}{space 2} .0095205{col 39}{space 1}   -1.19{col 48}{space 3}0.236{col 56}{space 4}-.0299531{col 69}{space 3} .0073664
{txt}{space 14} {c |}
{space 4}court_size {c |}
{space 11}25  {c |}{col 16}{res}{space 2} .0903791{col 28}{space 2} .1538117{col 39}{space 1}    0.59{col 48}{space 3}0.557{col 56}{space 4}-.2110864{col 69}{space 3} .3918445
{txt}{space 11}27  {c |}{col 16}{res}{space 2} .1922876{col 28}{space 2} .1469898{col 39}{space 1}    1.31{col 48}{space 3}0.191{col 56}{space 4} -.095807{col 69}{space 3} .4803823
{txt}{space 14} {c |}
{space 3}countrycode {c |}
{space 12}2  {c |}{col 16}{res}{space 2} .1553906{col 28}{space 2} .3331603{col 39}{space 1}    0.47{col 48}{space 3}0.641{col 56}{space 4}-.4975916{col 69}{space 3} .8083727
{txt}{space 12}3  {c |}{col 16}{res}{space 2} .4495187{col 28}{space 2} .2552496{col 39}{space 1}    1.76{col 48}{space 3}0.078{col 56}{space 4}-.0507613{col 69}{space 3} .9497987
{txt}{space 12}4  {c |}{col 16}{res}{space 2}-.0503735{col 28}{space 2} .4350672{col 39}{space 1}   -0.12{col 48}{space 3}0.908{col 56}{space 4}-.9030895{col 69}{space 3} .8023425
{txt}{space 12}5  {c |}{col 16}{res}{space 2}  .400285{col 28}{space 2}  .345299{col 39}{space 1}    1.16{col 48}{space 3}0.246{col 56}{space 4}-.2764886{col 69}{space 3} 1.077059
{txt}{space 12}6  {c |}{col 16}{res}{space 2} .1259091{col 28}{space 2} .4387579{col 39}{space 1}    0.29{col 48}{space 3}0.774{col 56}{space 4}-.7340405{col 69}{space 3} .9858587
{txt}{space 12}7  {c |}{col 16}{res}{space 2}-1.156438{col 28}{space 2} .5985162{col 39}{space 1}   -1.93{col 48}{space 3}0.053{col 56}{space 4}-2.329508{col 69}{space 3} .0166321
{txt}{space 12}8  {c |}{col 16}{res}{space 2} .1804696{col 28}{space 2} .3251122{col 39}{space 1}    0.56{col 48}{space 3}0.579{col 56}{space 4}-.4567385{col 69}{space 3} .8176778
{txt}{space 12}9  {c |}{col 16}{res}{space 2}-.1642691{col 28}{space 2} .5889266{col 39}{space 1}   -0.28{col 48}{space 3}0.780{col 56}{space 4}-1.318544{col 69}{space 3} .9900058
{txt}{space 11}10  {c |}{col 16}{res}{space 2} .1320779{col 28}{space 2} .2908019{col 39}{space 1}    0.45{col 48}{space 3}0.650{col 56}{space 4}-.4378833{col 69}{space 3} .7020391
{txt}{space 11}11  {c |}{col 16}{res}{space 2} .0184222{col 28}{space 2} .3500285{col 39}{space 1}    0.05{col 48}{space 3}0.958{col 56}{space 4}-.6676211{col 69}{space 3} .7044654
{txt}{space 11}12  {c |}{col 16}{res}{space 2} .6354656{col 28}{space 2} .5201768{col 39}{space 1}    1.22{col 48}{space 3}0.222{col 56}{space 4}-.3840622{col 69}{space 3} 1.654993
{txt}{space 11}13  {c |}{col 16}{res}{space 2} .0350535{col 28}{space 2} .3636738{col 39}{space 1}    0.10{col 48}{space 3}0.923{col 56}{space 4}-.6777341{col 69}{space 3}  .747841
{txt}{space 11}14  {c |}{col 16}{res}{space 2} .4671392{col 28}{space 2} .5319146{col 39}{space 1}    0.88{col 48}{space 3}0.380{col 56}{space 4}-.5753943{col 69}{space 3} 1.509673
{txt}{space 11}15  {c |}{col 16}{res}{space 2}-.0660431{col 28}{space 2}  .499671{col 39}{space 1}   -0.13{col 48}{space 3}0.895{col 56}{space 4} -1.04538{col 69}{space 3} .9132939
{txt}{space 11}16  {c |}{col 16}{res}{space 2} .1850112{col 28}{space 2} .3577684{col 39}{space 1}    0.52{col 48}{space 3}0.605{col 56}{space 4}-.5162019{col 69}{space 3} .8862243
{txt}{space 11}17  {c |}{col 16}{res}{space 2}        0{col 28}{txt}  (empty)
{space 11}18  {c |}{col 16}{res}{space 2} .7076951{col 28}{space 2} 1.007492{col 39}{space 1}    0.70{col 48}{space 3}0.482{col 56}{space 4}-1.266954{col 69}{space 3} 2.682344
{txt}{space 11}19  {c |}{col 16}{res}{space 2}        0{col 28}{txt}  (empty)
{space 11}20  {c |}{col 16}{res}{space 2} .1501339{col 28}{space 2} 1.187997{col 39}{space 1}    0.13{col 48}{space 3}0.899{col 56}{space 4}-2.178298{col 69}{space 3} 2.478566
{txt}{space 11}21  {c |}{col 16}{res}{space 2}        0{col 28}{txt}  (empty)
{space 11}22  {c |}{col 16}{res}{space 2}        0{col 28}{txt}  (empty)
{space 11}23  {c |}{col 16}{res}{space 2} 2.037917{col 28}{space 2} .7711583{col 39}{space 1}    2.64{col 48}{space 3}0.008{col 56}{space 4} .5264748{col 69}{space 3}  3.54936
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2} -1.52748{col 28}{space 2} .6287615{col 39}{space 1}   -2.43{col 48}{space 3}0.015{col 56}{space 4} -2.75983{col 69}{space 3}  -.29513
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *Model 3

. logit ecj_int1 c.sumcaseobs1##c.netint, vce(cluster case_celex)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2524.0191}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2483.7963}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2483.2105}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2483.2084}  
Iteration 4:{space 3}log pseudolikelihood = {res:-2483.2084}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      3861
{txt}{col 51}Wald chi2({res}3{txt}){col 67}= {res}     56.12
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-2483.2084{txt}{col 51}Pseudo R2{col 67}= {res}    0.0162

{txt}{ralign 80:(Std. Err. adjusted for {res:1599} clusters in case_celex)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}      ecj_int1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      z{col 48}   P>|z|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}sumcaseobs1 {c |}{col 16}{res}{space 2}-.2897598{col 28}{space 2} .4731862{col 39}{space 1}   -0.61{col 48}{space 3}0.540{col 56}{space 4}-1.217188{col 69}{space 3} .6376681
{txt}{space 8}netint {c |}{col 16}{res}{space 2} 2.573469{col 28}{space 2}   .69687{col 39}{space 1}    3.69{col 48}{space 3}0.000{col 56}{space 4} 1.207629{col 69}{space 3} 3.939309
{txt}{space 14} {c |}
{space 1}c.sumcaseobs1#{c |}
{space 6}c.netint {c |}{col 16}{res}{space 2} .5142148{col 28}{space 2} 2.333255{col 39}{space 1}    0.22{col 48}{space 3}0.826{col 56}{space 4}-4.058881{col 69}{space 3} 5.087311
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2}-.4504975{col 28}{space 2} .0708895{col 39}{space 1}   -6.35{col 48}{space 3}0.000{col 56}{space 4}-.5894384{col 69}{space 3}-.3115567
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *Model 4

. logit ecj_int1 c.sumcaseobs1##c.netint  i.agproint i.agantiint i.freegoods_guum i.agri_guum i.freework_guum i.estab_guum i.services_guum i.capital_guum i.transport_guum i.compet_guum i.tax_guum i.socialprov_guum i.environment_guum i.consum_guum c.lastelectionpartycompetition c.eu_support i.court_size i.countrycode , vce(cluster case_celex)

{txt}note: 17.countrycode != 0 predicts failure perfectly
      17.countrycode dropped and 1 obs not used

note: 19.countrycode != 0 predicts failure perfectly
      19.countrycode dropped and 17 obs not used

note: 21.countrycode != 0 predicts failure perfectly
      21.countrycode dropped and 2 obs not used

note: 22.countrycode != 0 predicts failure perfectly
      22.countrycode dropped and 1 obs not used

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2497.3435}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1583.2296}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1564.1492}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1564.0573}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1564.0573}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      3808
{txt}{col 51}{help j_robustsingular##|_new:Wald chi2(38)}{col 67}=          {res}.
{txt}{col 51}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-1564.0573{txt}{col 51}Pseudo R2{col 67}= {res}    0.3737

{txt}{ralign 80:(Std. Err. adjusted for {res:1587} clusters in case_celex)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}      ecj_int1{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      z{col 48}   P>|z|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}sumcaseobs1 {c |}{col 16}{res}{space 2}-1.866381{col 28}{space 2} .6563951{col 39}{space 1}   -2.84{col 48}{space 3}0.004{col 56}{space 4}-3.152892{col 69}{space 3}-.5798699
{txt}{space 8}netint {c |}{col 16}{res}{space 2} 4.165613{col 28}{space 2} .9091327{col 39}{space 1}    4.58{col 48}{space 3}0.000{col 56}{space 4} 2.383745{col 69}{space 3}  5.94748
{txt}{space 14} {c |}
{space 1}c.sumcaseobs1#{c |}
{space 6}c.netint {c |}{col 16}{res}{space 2}-5.234668{col 28}{space 2} 2.388357{col 39}{space 1}   -2.19{col 48}{space 3}0.028{col 56}{space 4}-9.915762{col 69}{space 3}-.5535731
{txt}{space 14} {c |}
{space 4}1.agproint {c |}{col 16}{res}{space 2} 3.565627{col 28}{space 2} .1303312{col 39}{space 1}   27.36{col 48}{space 3}0.000{col 56}{space 4} 3.310183{col 69}{space 3} 3.821072
{txt}{space 3}1.agantiint {c |}{col 16}{res}{space 2} .5402789{col 28}{space 2} .1356878{col 39}{space 1}    3.98{col 48}{space 3}0.000{col 56}{space 4} .2743356{col 69}{space 3} .8062221
{txt}1.freegoods_~m {c |}{col 16}{res}{space 2}-.1386048{col 28}{space 2} .1797661{col 39}{space 1}   -0.77{col 48}{space 3}0.441{col 56}{space 4}-.4909398{col 69}{space 3} .2137302
{txt}{space 3}1.agri_guum {c |}{col 16}{res}{space 2}-.0916093{col 28}{space 2} .1790944{col 39}{space 1}   -0.51{col 48}{space 3}0.609{col 56}{space 4}-.4426278{col 69}{space 3} .2594092
{txt}1.freework_g~m {c |}{col 16}{res}{space 2} .5628244{col 28}{space 2} .2073266{col 39}{space 1}    2.71{col 48}{space 3}0.007{col 56}{space 4} .1564718{col 69}{space 3}  .969177
{txt}{space 2}1.estab_guum {c |}{col 16}{res}{space 2}-.1582874{col 28}{space 2} .2018491{col 39}{space 1}   -0.78{col 48}{space 3}0.433{col 56}{space 4}-.5539044{col 69}{space 3} .2373295
{txt}1.services_g~m {c |}{col 16}{res}{space 2} .2567002{col 28}{space 2} .2220363{col 39}{space 1}    1.16{col 48}{space 3}0.248{col 56}{space 4} -.178483{col 69}{space 3} .6918833
{txt}1.capital_guum {c |}{col 16}{res}{space 2} .2753363{col 28}{space 2} .2630954{col 39}{space 1}    1.05{col 48}{space 3}0.295{col 56}{space 4}-.2403212{col 69}{space 3} .7909938
{txt}1.transport_~m {c |}{col 16}{res}{space 2}-.3796328{col 28}{space 2} .2801041{col 39}{space 1}   -1.36{col 48}{space 3}0.175{col 56}{space 4}-.9286268{col 69}{space 3} .1693612
{txt}{space 1}1.compet_guum {c |}{col 16}{res}{space 2} -.476609{col 28}{space 2} .1756957{col 39}{space 1}   -2.71{col 48}{space 3}0.007{col 56}{space 4}-.8209663{col 69}{space 3}-.1322517
{txt}{space 4}1.tax_guum {c |}{col 16}{res}{space 2} .3586551{col 28}{space 2} .1812774{col 39}{space 1}    1.98{col 48}{space 3}0.048{col 56}{space 4} .0033579{col 69}{space 3} .7139523
{txt}1.socialprov~m {c |}{col 16}{res}{space 2} .6872117{col 28}{space 2} .2185965{col 39}{space 1}    3.14{col 48}{space 3}0.002{col 56}{space 4} .2587704{col 69}{space 3} 1.115653
{txt}1.environmen~m {c |}{col 16}{res}{space 2}  .471052{col 28}{space 2} .2534087{col 39}{space 1}    1.86{col 48}{space 3}0.063{col 56}{space 4}  -.02562{col 69}{space 3}  .967724
{txt}{space 1}1.consum_guum {c |}{col 16}{res}{space 2} .0128059{col 28}{space 2} .2449852{col 39}{space 1}    0.05{col 48}{space 3}0.958{col 56}{space 4}-.4673562{col 69}{space 3}  .492968
{txt}lastelection~n {c |}{col 16}{res}{space 2} .1903741{col 28}{space 2} 1.071433{col 39}{space 1}    0.18{col 48}{space 3}0.859{col 56}{space 4}-1.909597{col 69}{space 3} 2.290345
{txt}{space 4}eu_support {c |}{col 16}{res}{space 2} -.011309{col 28}{space 2} .0095129{col 39}{space 1}   -1.19{col 48}{space 3}0.235{col 56}{space 4}-.0299539{col 69}{space 3} .0073359
{txt}{space 14} {c |}
{space 4}court_size {c |}
{space 11}25  {c |}{col 16}{res}{space 2} .0858693{col 28}{space 2} .1540517{col 39}{space 1}    0.56{col 48}{space 3}0.577{col 56}{space 4}-.2160664{col 69}{space 3} .3878051
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